Daniel W. Surry and Andy K. Stanfield

Editor’s Note: This chapter was originally published in a previous open access book, The Foundations of Instructional Technology.

Surry, D. W., & Stanfield, A. K. (2008). Performance technology. In M. K. Barbour & M. Orey (Eds.), The Foundations of Instructional Technology. Retrieved from http://projects.coe.uga.edu/itFoundations/

Overview and Background

Performance is probably the most important word in any organization. Whether an organization is a global giant, a mid-sized regional firm, or a small local company, the performance of the people within the organization plays a critical role in its success. Performance is the key to success for organizations in every sector including business and industry, non-profit, government, military, and education. While everyone agrees that performance is an essential part of organizational success, there is disagreement about how performance is defined and measured and, most importantly, the best strategies for improving performance.

There are many different definitions for performance. If you ask 10 people to give their definition of performance, you are likely to get a wide range of answers. Some people will define performance as the goods and services provided by an organization while others will mention terms such as profitability, productivity, and efficiency. Stolovitch (2007) provides one of the clearest and most concise definitions of performance. He defines performance as a “valued accomplishment derived from costly behavior” (p. 136). This definition highlights the fact that, in a business context at least, performance should be linked to desirable organizational goals. Other definitions (e.g., Torraco, 1999) often point out that performance must be based on a defined, observable, and measureable standard. Rothwell (1996b) stresses that performance is different from behavior or activity because the emphasis is not on what people are doing, but on the end results. Swanson (1999b) adds that performance is determined by actual accomplishments, not by the potential or capacity for accomplishment. From these definitions we can think of performance as the tangible, measureable, desired outcomes resulting from the efforts of people within an organization.

There are also many definitions of technology. Most people would define technology as a tool, such as a hammer, a telephone, or a computer. However, current definitions of technology usually describe technology not only as a tool, but also as techniques and practices. Broader definitions of technology (e.g., Hughes, 1996) include the associated technical and social systems in which a technological tool is used. The broadest definitions of technology (e.g., Cardwell, 1995) stress the scientific and systemic knowledge that is required for the effective development and use of any technology. Performance technology, therefore, is a field of practice that uses various tools, processes, and ideas in a scientific, systematic manner to improve the desired outcomes of individuals and organizations.

Performance technology, also commonly referred to as human performance technology (HPT), performance systems (PS), or performance improvement (PI), among other terms, represents a fundamental shift in thinking about how to improve performance. Traditional views have tended to focus on training as an organization’s primary tool for performance improvement. For example, under the traditional view, if the quality of a product was found to be below acceptable standards at a factory, workers would be given additional training to improve their skill levels and, as a result, improve the quality of the products. There are, however, a number of problems with this traditional view of training. The most compelling and most widely cited argument against the traditional view is that the skills and knowledge acquired during training often have limited transfer to the worksite. In fact, training is now usually seen as a short term solution to a performance problem (Rothwell, Lindholm, & Wallick, 2003) and often the performance improvement strategy of “last resort” (Rothwell, 1996b, p. 252).

Performance technology, on the other hand, takes a more holistic view to identify performance problems and develop solutions to those problems. In the above example, performance technologists would look for all of the possible root causes of the factory’s quality problem, including the tools the workers use, the organizational culture, motivational issues, supporting processes, and management policies. From a performance technology perspective, training is one of many possible solutions to a performance problem, not the only, and often not the best, solution. The fundamental paradigm shift of performance technology is, therefore, to change from a focus on learning to a focus on performance (Rosenberg, 1995).

Historical Development

Performance Technology is a fairly new career field. The growth of performance technology began in the 1960s and expanded greatly throughout the intervening decades. Thomas F. Gilbert is credited by Stolovitch (2007) as being the father of performance technology as a result of his research related to workplace performance in the 1960s and 1970s. Conn and Gitonga (2004) note that the shift in focus from a traditional training paradigm to performance technology began to be seen in the education literature in the “late 1970s and early 1980s” (p. 16). This shift toward performance technology continued to grow in the 1980s and 1990s as the rapidly expanding power of information technology created a global, knowledge-based economy (Molenda & Pershing, 2004).

Performance technologists employ a wide array of theories and practices from diverse fields such as education, business, and psychology to identify and address performance problems (Hotek & White, 1999). Stolovitch and Keeps (1999) include general systems theory and behavioral psychology as major antecedents to the field of performance technology. Other writers (e.g., Rosenberg, Coscarelli, & Hutchison, 1999) include instructional systems design, ergonomics, feedback, and organizational change theories among the many contributors to the theoretical foundation of performance technology.

In the remainder of this chapter, we will provide an overview of the field of performance technology. We will begin with a brief discussion of the process by which performance technologists identify and address performance problems within an organization. This discussion will include performance analysis, performance drivers, interventions, and evaluation. Following this, we will describe electronic performance support systems (EPSS), perhaps the most widely discussed and potentially powerful tool for improving performance. We will then briefly discuss several trends which will affect the future of performance technology. We will conclude this chapter with a discussion of professional resources related to performance technology including professional organizations, conferences, journals, and books.

Process of Performance Technology

Performance technologists use a systematic, scientific process to identify and address organizational performance problems. Several authors (e.g., Deterline & Rosenberg, 1992; Hotek & White, 1999; Rothwell, 1996) have presented theoretical models of the performance technology process. While most models differ in regard to specific details and terminology, they all seem to include four broad phases. These phases are typically referred to as Performance Analysis, Performance Drivers, Interventions, and Evaluation. Performance analysis is the process of determining the current level of performance related to a task and, often, the optimal, or desired, level of that performance. Performance drivers are broad categories of factors that impact performance. Interventions are actions taken by an organization to alter one or more of the performance drivers, usually for the purpose of improving performance. Evaluation refers to the process of determining the effectiveness of a performance intervention as measured by the attainment of desired levels of performance. Each of these four common phases of performance technology models will be discussed in more detail in this section.

Performance Analysis

Performance analysis is usually considered the first step in the process of performance technology. In the most basic sense, performance analysis is the process of working with an organization to determine current levels of performance, define performance goals, and identify factors that are facilitating or impeding attainment of those goals (Rossett, 1999a,1999b). Broadly stated, there are two categories of information that are sought in a performance analysis. The first category of information provides a holistic, multi-perspective view of the organization, its capabilities, and goals. Included in this category is information about the organization itself, the current (or actual) level of performance, and the desired (or optimal) level of performance (Rossett, 1999a). The second category of information relates to factors that are serving to facilitate or impede attainment of the optimal level of performance (Rossett, 1999a).

Performance analysis should be a data-driven process. Any qualitative or quantitative data that could help to inform either of the two categories of information discussed above should be identified and, if practical, collected and analyzed. Performance technologists typically employ a wide array of data collection methods during the performance analysis process including interviews, surveys, observation, and document analysis (Van Tiem, Moseley, & Dessigner, 2001).

Those who are familiar with the field of instructional design and development will notice that performance analysis appears similar to the process of training needs assessment. While there are similarities, especially in the determination of current and optimal levels of performance, Rossett (1999a, 1999b) differentiates between training needs assessment and performance analysis. One key difference is that many writers consider training needs assessment to be one of several possible follow up activities to a performance analysis, used only when training is identified as necessary to addressing a performance problem (e.g., Rossett, 1999b).

Performance Drivers

As mentioned above, a performance analysis tries to identify factors which facilitate or impede performance. These factors are often referred to as performance drivers. Obviously, an almost infinite number of factors can affect a person’s performance on a task. Performance can be affected by a variety of external factors such as work conditions, the availability of necessary technology, staffing patterns, social and societal issues, salary, and the physical environment, among many others. In addition, a wide number of internal factors such as motivation, self efficacy, knowledge, experience, and commitment can affect a person’s performance. While there are numerous factors that can impact performance, most writers group the drivers into four broad categories: Skills and Knowledge; Motivation, Environment, and; Incentives. Each of these will be discussed in more detail in the following section.

Skills and Knowledge

Skills and knowledge is the driver that people most commonly associate with performance. This category includes all of the intellectual and physical operations that a person must complete while performing a task. In order to perform even the simplest task effectively, a person has to be able to understand the task, make decisions about the task, and execute a number of physical operations and processes related to the task. For example, in order to cook even a basic meal, a person must have an amazing array of skills and knowledge. A person must list the proper ingredients, or at least be able to read a recipe, be able to measure, be able to tell time, know how to operate an oven, know where to locate utensils and cookware, be able to prepare and season the ingredients, be able to use a variety of knives and other food processing equipment, know how to combine and cook the various elements, and be able to assemble and present the finished meal. If a person has a lack of skills or knowledge in any one of those areas, the quality of the meal will suffer.

There are several well-known methods for describing the different types of skills and knowledge that can be learned. One of the most comprehensive breaks skills and knowledge into five domains: verbal information, intellectual skills, psychomotor skills, attitudes, and cognitive strategies (Dick, Carey, & Carey, 2005). When a lack of skills and knowledge has been found to contribute to a performance problem, training, or some other form of instructional intervention, should be employed to address the problem.


A person will not perform a task, or will not perform the task to an acceptable level, unless they have a desire to perform the task. We can all think of examples when we ourselves have had the skills and knowledge required to perform a task, but lacked the required level of motivation. Anyone who has ever left dirty dishes in the sink, dirty clothes in the hamper, or a dirty car in the driveway has been guilty of a lack of motivation. Washing dishes, doing laundry, and cleaning a car are not difficult tasks, but without motivation, they will not be accomplished.

The literature is filled with theories about the factors that affect motivation. For example, Rossett (1999a) writes that motivation is made up of two factors–valuing and confidence. She states that a worker has to be aware of the value of a task and be confident that they can perform a task in order to be motivated to complete the task. Keller (1999) states that motivation has four major components: Attention, relevance, confidence, and satisfaction. He writes that in order to motivate workers, we must ensure that they are aware of the task, feel the task is relevant to their personal and professional goals, feel confident that they can complete the task, and receive a sense of satisfaction as a result of properly completing the task. When motivation is determined to be negatively affecting performance, personal and organizational problems are often the cause (Rothwell, 1996).


All tasks are performed within a unique environment. The task environment includes all of the tools, facilities, policies, social interactions, cultures, traditions, practices, and other conditions present within an organization at the time a task is to be performed. Continuing with our earlier example of cooking a meal, most of us would agree that it would be easier to prepare a meal if we had a modern, clean, well-stocked kitchen in which to work. We would also agree that cooking a meal would be easier if we were working with a group of talented, supportive, friendly, and experienced cooks and had available to us a well-defined, effective, and efficient process for preparing, cooking, and presenting the meal. This shows the importance of the environment driver.

Factors relating to this driver are often broken down into three sub-drivers–environment, tools, and processes (e.g., Rossett, 1999a). The sub-driver of environment can be thought of as synonymous with corporate culture. An organization’s culture is pervasive and is comprised of all the values, role models, rites and rituals, symbols, and artifacts of an organization (Van Tiem, Moseley, & Dessigner, 1999). The culture of an organization impacts organizational effectiveness and is critical to the ultimate success of an organization (Lineberry & Carleton, 1999).

The sub-driver of tools is synonymous with an organization’s technological infrastructure. Technological infrastructure includes the tools and technologies that directly impact an organization’s mission, known as primary technologies, as well as all associated and supporting technologies, known as secondary technologies (Surry, Ensminger, & Haab, 2005). In our cooking example, tools in a large commercial kitchen would include not only technologies directly related to food preparation, such as ovens, grills, blenders, and cookware, but also associated technologies such as refrigeration and storage systems, lighting, software for inventory control, cleaning supplies, fire suppression systems, and heating, ventilation, and air conditioning technologies, to name only a few. It is important to analyze all of the interconnected technologies within an organization, both primary and secondary, when looking at this performance driver.

The sub-driver of processes includes organization policies, methods, rules, and regulations. Rothwell (1996b) differentiates between policies and procedures. He writes that a policy “coordinates the activities of different organization functions or work methods to achieve common and desired ends” (p. 222). A procedure is an often-detailed set of interconnected steps needed to carry out a policy. Ambiguous, outdated, inconsistent, or contradictory policies and procedures are a common reason for organizational performance problems.


Incentives are the external benefits that one receives for completing a task. In order to be most effective, incentives should be available to all workers, linked to specific performance goals, awarded in a timely manner, and fairly and equitably distributed (Van Tiem, Moseley, & Dessigner, 1999). Incentives can be monetary or other types of rewards, such as recognition, that encourage workers to increase productivity. Traditionally, incentives for senior level workers have also included a number of other awards and services, such as bonuses and stock options (Stolovich & Keeps, 1999). Incentives will likely vary by business type, country, and culture. There are a number of common problems related to incentives that result in reduced performance. These common problems include incentives which conflict with each other; incentives which reward undesired, or less desired, performances; and the lack of incentives altogether (Rossett, 1999a).


An intervention is a purposeful act intended to improve performance. As we have seen, there are a great number of possible causes for performance problems. Therefore, there are also a great number of possible interventions to improve performance. These can range from job aids, mentoring, simulations, and work groups to action learning and process redesign (Landon, Whiteside, & McKenna 1999). There are many ways to group and categorize interventions. Perhaps the most common method is to divide interventions into two broad groups, instructional interventions and noninstructional interventions (Stolovitch & Keeps, 1999). Instructional interventions are typically used when a lack of skills and knowledge is determined to be the cause of the performance problem. Noninstructional interventions are used when the performance problem is not caused by a lack of skills and knowledge.

Instructional interventions are designed to provide workers with the knowledge and skills they will need to perform at a desired level. Instructional interventions can be further divided into two sub-groups. The first sub-group is direct instruction. Direct instruction provides targeted skills and knowledge to learners in a relatively formal, usually highly structured environment. By far the most common example of direct instruction is live classroom training (Langdon, 1999; Yelon, 1999). Other examples of direct instruction include computer-based training, instructional videos, and instructional manuals. It should be noted that instructional interventions are also sometimes used when motivation is determined to be the cause of a performance problem as increased knowledge and skill can lead to improved confidence and, as a result, improve motivation (Rossett & Gautier-Downes, 1991).

Indirect instruction is the second sub-group of instructional interventions. Indirect instruction is designed to provide workers with the skills and knowledge they will need in an environment other than traditional training. A job aid is perhaps the most commonly used and cost efficient example of indirect instruction (Ellison, 1999). Job aids provide workers with important knowledge while saving time and money, reducing or eliminating the need for training, and improving transfer (Rossett & Gautier-Downes, 1991). Other examples of indirect instruction include coaching, mentoring, and on-the-job training (Langdon, Whiteside, & McKenna, 1999).

Noninstructional interventions are typically used when the cause of a performance problem is not a lack of skills and knowledge. There are, of course, a large number of noninstructional interventions. Most noninstructional interventions fall under the broad framework of organization design (Dean, 1999). This typically includes activities such as conflict management, organizational change, process redesign, performance appraisal, reward and recognition programs, and strategic planning. Other examples of noninstructional interventions include human resource selection and development, feedback, workplace redesign, and improved compensation systems (Stolovitch & Keeps, 1999).

Types of Performance Changes

Langdon, Whiteside, and McKenna (1999) list four types of performance changes that interventions can be used to facilitate. These performance changes are: establish, improve, maintain, or extinguish. Establishing performance is defined as creating or starting a desired performance where one does not currently exist (Langdon, Whiteside & McKenna,1999). An example of establishing a performance might be teaching employees the proper procedure for using a new software package.

Improving performance is defined as enhancing an existing performance based on a variety of criteria, such as speed, quality, or quantity (Langdon, Whiteside & McKenna,1999). Performance should be improved when a previously acceptable standard of performance has fallen below acceptable standards or when the standard for acceptable performance has been raised.

Maintaining performance is defined as fostering the continuation of an acceptable existing performance (Langdon, Whiteside & McKenna,1999). While we typically think of using a performance intervention in response to a performance problem, interventions should also be used as part of an ongoing process of maintaining performance.

Extinguishing performance is defined as ending an existing performance that is unwanted or undesired (Langdon, Whiteside & McKenna,1999). Undesired performances can either be extraneous or unnecessary performances or performances that were once desired but have subsequently become undesired. For example, smoking, cursing, or taking frequent personal calls on a cell phone are all examples of extraneous or unnecessary performances which may need to be extinguished. An example of a once-desired performance that is now undesired is mouth-to-mouth breathing for the victim during cardiopulmonary resuscitation (CPR). While this was once a desired behavior, the American Heart Association now recommends compressions only. Those trained in the traditional CPR methods may need an intervention to extinguish the performance of mouth-to-mouth breathing.

Levels of Performance

Langdon, Whiteside and McKenna (1999) define four levels within an organization that can be targeted for performance interventions. These are unit, work group, process, and individual. A unit is the broadest level of an organization, such as a factory, store, or corporate headquarters. A work group is a subset of a business unit, such as a design team or other group that has a closely-related task. A process is a group of interrelated steps that result in a specific output. An individual is any one person who is part of a work group or contributes to a process.

When selecting an intervention, it is important to consider three factors. The first is the cause of the performance problem. Certain interventions are most appropriate depending if the performance problem is caused by a lack of skills or knowledge, environment, tools or processes, motivation, or incentives. The second factor to consider when selecting an intervention is the type of performance change desired. The appropriateness of many interventions is dependent upon whether you intend to establish, improve, maintain, or extinguish a certain performance (Langdon, Whiteside & McKenna, 1999). The third factor to consider when selecting an intervention is the organizational level to be addressed by the intervention. Certain interventions are most effective at the individual level while others may be most appropriate only at the unit, process, or work group level (Langdon, Whiteside & McKenna).


An intervention is a purposeful act intended to affect performance. Evaluation is intended to determine if a performance intervention had the intended impact on performance. For performance technology, two of the main concepts are concerned with the Kirkpatrick model and with Return-on-Investment (ROI).

The Kirkpatrick model of Training Evaluation arose from Kirkpatrick’s dissertation in the 1950s. It has been in continuous use ever since. The Kirkpatrick model has four levels: reaction, learning, behavior, and results (Kirkpatrick, 1998).

The reaction level gauges how respondents feel about a performance intervention. This is the most commonly used level in Kirkpatrick’s model. Most often, attitude surveys will be given to the workers to gain an understanding of their initial reactions in regard to an intervention. Reaction can also be determined with interviews, focus groups, or observation. By looking at the workers’ basic reactions, many modifications may be easily made to the intervention. For example, a performance technologist may interview workers who have been among the first to take part in an organization-wide training program to determine how to make the program more interesting, relevant, or useful and then incorporate that information into subsequent programs.

The learning level looks at how much learning actually took place after the performance intervention. This aspect of Kirkpatrick’s model is most commonly associated with instructional interventions. Learning is most commonly determined by comparing performances on pretests with those on posttests. Determining the amount of learning that has occurred can give a performance technologist a strong understanding of the strengths and areas for improvement of their instructional interventions.

The behavior level of Kirkpatrick’s model is designed to determine transfer. Transfer can be defined as how the desired performance actually changed as a direct result of an intervention. Observations might be utilized to gather data. Other methods might include checklists, demonstrations, and document analysis, among others. By focusing on actual changes in behavior, the evaluators are able to assess the long-term, practical effects of an intervention.

The fourth level of Kirkpatrick’s model is results. At this level, evaluators look at the costs and benefits of an intervention to determine if the performance intervention had a positive result on the overall performance of an organization. Some might consider this the most important level of the Kirkpatrick model because of its focus on costs and resources and overall impact, as such, it should be implemented in performance settings more often than current usage.

A concept that is somewhat related to Kirkpatrick’s fourth level is return on investment (ROI). ROI is an analysis of the overall value, costs, and benefits of a performance improvement activity to an organization. It is commonly believed that performance improvement interventions do not result in a high return on investment (Swanson, 1999a). However, this could be due to the fact that our ability to accurately determine all of the ways that performance improvement interventions result in return on investment for an organization is still at a very elementary level. Fairly and accurately determining return on investment will become increasingly more important to the field of performance technology in the future (Stolovitch, 2007).

Electronic Performance Support Systems

One of the most important and widely discussed tools for improving performance is an Electronic Performance Support System (EPSS). An EPSS is an on-demand, computer-based system that integrates the information, training, and tools needed to complete a task and provides them to the user at the performance site (Van Tiem, Moseley, & Dessinger, 2001). Barry Raybould and Gloria Gery are considered two of the main pioneers of the EPSS movement (McKay & Wager, 2007). EPSSs are considered powerful tools and are attractive to many organizations because they reduce or eliminate the need for training and change the focus from knowledge to performance (Winer, Rushby, & Vazquez-Abad, 1999).

At a basic level, an EPSS is a tool that guides the worker through a task by providing information, guidance, and coaching (Gery & Jezsik, 1999). A more advanced EPSS will also provide a database of information, access to expert advice, and even training to the workers (Gery & Jezsik). It is important to note that an EPSS is intended to provide support to the worker at the jobsite and at the time when the support is needed.

EPSS Elements

Electronic performance support systems usually have a variety of elements. Gery and Jezsik (1999) discuss five common elements of an EPSS. These five elements are task-structuring, knowledge, data, tools, and communication.

Task structuring refers to the EPSS providing the user with a clear, step-by-step process for completing a task (Gery & Jezsik, 1999). The knowledge element combines text, sound, video, and other media elements to provide the user with the verbal information, intellectual skills, rules, and concepts they will need to complete the task (Gery & Jezsik). To be most effective, the knowledge element must be organized in a logical manner and searchable (McKay & Wager, 2007). Data refers to current, or even real-time, information needed by a worker to complete a task (Gery & Jezsik). For example, an EPSS used by a stock broker would likely include real-time data about the overall market and prices of specific stocks. The element of tools refers to tasks that can be accomplished, in full or in part, by using the EPSS (Gery & Jezsik). Tasks could be as simple as making basic calculations or as complicated as creating and interpreting complex forecasting models. The tools available through an EPSS can be employed by the user or automatically employed by the system (McKay & Wager).

Most electronic performance systems in use today include only a few of the elements discussed above (McKay & Wager, 2007). The high cost of creating and maintaining an EPSS is one reason for the lack of widespread use of fully featured EPSSs at this time. Another reason is the need for organizations to adapt existing policies, structures, and procedures to make effective use of an EPSS (Van Tiem, Moseley, & Dessigner, 2001). In spite of these issues, it seems likely that as technology continues to become more powerful and more research related to performance improvement is conducted, electronic performance support systems will continue to evolve, become more powerful, cheaper and easier to develop and use, and more flexible. As a result, EPSSs will likely play an increasingly important role in the field of performance technology.

Future Trends

There are several trends which will affect the field of performance technology in the future. One of the major trends affecting many areas of society is asynchronous e-learning (Rossett, 2004). With the increasing speed and capability of the Internet, instructional interventions will be delivered less frequently in traditional classrooms and more frequently to the worker’s home, desktop, or workstation. This will necessitate a rethinking of what is meant by the term “direct instruction” and require new methods for effectively incorporating interaction, motivation, and assessment into instructional interventions.

Web 2.0 technologies will also impact the future of performance technology. Virtual worlds such as Second Life are creating new and innovative spaces for organizations to provide performance support. These immersive micro-worlds could be used in countless ways to improve performance, from increasing communication to improving motivation to providing virtual mentoring and on-the-job training. Many companies have a presence in Second Life, and some countries even have virtual embassies in this immersive world of avatars. The concept of virtual worlds in performance technology will only gain in importance as time and technology advance.

Another trend that will affect performance technology is the rising number of younger workers who are entering the workforce. For example, Neomillennials are young learners who have grown up with technology and have developed a different learning style than previous generations (Baird, 2005). These new employees and workers seek both individual and group experiences in learning and work, and they enjoy incorporating social networking software into their lives. Performance technologists will have to develop new theories and practices to make performance support more relevant and useful to these new workers.

Fortunately, there are many new technologies that may be used to increase performance by meeting the needs of changing workers, including blogs, podcasts, and wikis. Wikis are websites that are capable of being edited by users. There are countless performance applications for these technologies, especially in team-based projects that require multiple simultaneous drafts. Blogs also have great potential for performance technology. They can be used as a means for employees and members of design teams to post their accomplishments, problems, and drafts with minimal delays or barriers. Podcasts are syndicated audio or video files that may be stored and played with great user control (Farkas, 2006). Audio files and podcasts might be another way to increase usage, motivation, and to prevent or correct performance problems.

Another trend that appears to be emerging in performance technology concerns digital game-based learning. Prensky (2001) sees digital games and simulations as one of the leading trends for future designers, with more digital games to increase workers’ performance as the technology becomes more diffused throughout society, in addition to becoming easier and more affordable. Eventually, digital game-based learning may become the norm in providing instructional performance interventions in the business world.

There are many other societal, professional, and technological trends that will affect the future of performance technology. The use of electronic performance support systems, simulations, reusable learning objects, and knowledge management systems will continue to grow and impact performance. There will likely be continued efforts to establish, define, and improve the professional preparation and certification of performance technologists. Finally, it is likely that organizations will continue to shift their focus away from the traditional emphasis on training toward a continued and growing emphasis on performance improvement, especially on noninstructional interventions.

Professional Resources

There are many resources available to assist those who are interested in learning more about the field of performance technology. In this section, we will discuss a few of the largest professional associations related to performance technology, describe several annual conferences that performance technologists commonly attend, and list a number of important books and journals related to the field.

Professional Associations

A professional association is an organization devoted to furthering the goals and development of a profession as well as providing professional development and networking opportunities for members of the association. The largest professional organizations focusing on the field of performance technology are the American Society for Training and Development (ASTD) and the International Society for Performance Improvement (ISPI). According to their website, ASTD was founded in 1944 and is the largest organization in the world related to workplace learning and performance with members from over 100 countries. According to their website, ISPI was founded in 1962 and has over 10,000 members in over 40 countries.

Some performance technologists are members of the Association of Educational Communications and Technology (AECT), specifically the Division of Training and Performance. Still other performance technologists belong to the American Educational Research Association (AERA), specifically special interest groups related to learning sciences, learning environments, instructional technology, and organizational theory.

Most professional organizations have local chapters in larger cities that are active throughout the year and offer locally focused networking and professional development opportunities. For example, ISPI has chapters in a number of U.S. cities, including Los Angeles, San Diego, Atlanta, and St. Louis and international chapters in countries including Canada, Australia, Japan, and South Africa. ASTD has over 140 chapters located in every U.S. state and in Puerto Rico.

More information about each of the professional organizations discussed in this section can be found online at:
American Educational Research Association (AERA) http://aera.net
American Society for Training and Development (ASTD) http://astd.org
Association for Educational Communications and Technology (AECT) http://aect.org
International Society for Performance Improvement (ISPI) http://ispi.org


Professional conferences provide valuable opportunities to learn more about a field. A professional conference is usually associated with a professional organization, such as ASTD or ISPI. Conferences are usually held once a year, often in a different city, and are often organized around a central theme. Conferences typically include hands-on workshops, presentations on topics relevant to the profession, featured speakers, and social events.

The most important conferences related to the field of performance technology include the ASTD International Conference & Exposition and ISPI’s Fall Conference and THE Performance Improvement Conference. Annual conferences by AECT and AERA will also typically include a number of presentations relevant to performance technology.


Even though performance technology is a relatively young field, several books have already come to be seen as foundational resources. A complete list of important books related to performance technology is beyond the scope of this chapter, but a few of the most widely cited books include:

  • Fundamentals of Performance Technology (2004) by Darlene Van Tiem, James L. Moseley, and Joan C. Dessinger, published by the International Society for Performance Improvement.
  • Handbook of Human Performance Technology (2006) by James A. Pershing, published by the International Society for Performance Improvement.
  • HPI Essentials (2002) by George Piskurich, published by ASTD Press.
  • Intervention Resource Guide: 50 Performance Improvement Tools edited by Danny G. Langdon, Kathleen S. Whiteside, and Monica M. McKenna, published by Pfeiffer.
  • First Things Fast: A Handbook for Performance Analysis (1999) by Allison Rossett, published by Pfeiffer.
  • Human Competence: Engineering Worthy Performance by Thomas F. Gilbert, originally published in 1978 by McGraw-Hill (2007 edition published by Pfeiffer).


A number of journals, usually published by professional organizations, are seen as important to the field of performance technology. These journals publish articles on various trends, problems, and innovative approaches to performance technology. The following three journals are among the most widely circulated and well-respected journals related to performance technology:

    • Performance Improvement Journal is published 10 times a year by the International Society for Performance Improvement and John Wiley & Sons, Inc. (Articles tend to be practitioner and application oriented)
    • Performance Improvement Quarterly is a peer-reviewed scholarly journal published by the International Society for Performance Improvement

T+D (Training + Development), is a monthly magazine published by the American Society for Training & Development

In addition, a number of journals published by the Association for Educational Communications and Technology, including Educational Technology Research and Development, TechTrends, and Quarterly Review of Distance Education, also include articles related to performance technology (Conn & Gitonga, 2004).


Performance is the key to success in any organization. Performance technology is a valuable tool that organizations can use to improve their productivity and profitability. Performance technology represents a fundamental change in how to improve performance. Instead of relying on training as the primary method for improving performance, performance technology takes a holistic view of all the possible causes of a performance problem and recommends the most appropriate solutions. This change in focus from learning to performance has many benefits to organizations including cost savings and enhanced transfer of skills to the worksite. From its beginnings in the early 1960s until now, the field of performance technology has enjoyed a remarkably rapid and wide acceptance. As the theories of performance improvement become more refined, as technology continues to expand, and as the benefits of this new paradigm become more widely known, it is likely that performance technology will continue to play an increasingly important role in all sectors of the economy.

Application Exercises

  • Consider a task environment that you are familiar with. It could be a home office, living room, classroom, or lab. How do the sub-drivers of the environment (environment, tools, and processes) affect performance within the environment?
  • The chapter discusses several aspects under Process of Performance Technology section. Take some time and try to analyze your target teaching setting and the learners. For example, what is the environment, what are your learners’ motivation, and what types of skills and knowledge can be learned?


Baird, D, E., & Fisher, M. (2005-6). Neomillennial user experience design strategies: utilizing social networking media to support “always on” learning styles. Journal of Educational Technology Systems, 34(1) 5–32.

Brethower, D. M. (1999). Human performance interventions of a noninstructional nature. In H. D. Stolovitch & E. J. Keeps (Eds.), Handbook of human performance technology (2nd ed., pp. 319–320). San Francisco: Jossey Bass/Pfeiffer.

Cardwell, D. (1995). The Norton history of technology. New York: Norton & Company.

Conn, C. A., & Gitonga, J. (2004). The status of training and performance research in AECT journals. TechTrends, 48(2), 16–20, 78.

Dean, P. J. (1999). Designing better organizations with human performance technology and organizational development. In H. D. Stolovitch & E. J. Keeps (Eds.), Handbook of human performance technology (2nd ed., pp. 321–334). San Francisco: Josey Bass/Pfeiffer.

Deterline, W. A., & Rosenberg, M. J. (1992). Workplace productivity: Performance technology success stories. Washington, DC: International Society for Performance Improvement.

Dick, W., Carey, L., & Carey, J. O. (2005). The systematic design of instructions (5th ed.). Boston: Pearson.

Ellison, P. H. (1999). Job aids. In H. D. Stolovitch & E. J. Keeps (Eds.), Handbook of human performance technology (2nd ed., pp. 430–441). San Francisco: Jossey Bass/Pfeiffer.

Farkas, B. G. (2006). Secrets of podcasting. Berkeley, CA: Peachpit Press.

Gery, G., & Jezsik, L. (1999). Electronic performance support system (EPSS). In D. G. Langdon, K. S. Whiteside, & M. M. McKenna (Eds.), Intervention resource guide: 50 performance improvement tools (pp. 142–148). San Francisco: Jossey Bass/Pfeiffer.

Lineberry, C. S., & Carleton, J. R. (1999). Designing better organizations with human performance technology and organizational development. In H. D. Stolovitch & E. J. Keeps (Eds.), Handbook of human performance technology (2nd ed., pp. 335–350). San Francisco: Jossey Bass/Pfeiffer.

Hotek, D. R., & White, M. R. (1999). An overview of performance technology. The Journal of Technology Studies, 25(1), 43–50.

Hughes, T. P. (1996). Technological momentum. In M. R. Smith & L. Marx (Eds.), Does technology drive history? The dilemma of technological determinism (pp. 101–113). Cambridge, MA: The MIT Press.

Keller, J. M. (1999). Motivational systems. In H. D. Stolovitch & E. J. Keeps (Eds.), Handbook of human performance technology (2nd ed., pp. 373–394). San Francisco: Jossey Bass/Pfeiffer.

Kirkpatrick, D. L. (1998). Evaluating training programs (2nd ed.). San Francisco: Berrett-Koehler.

Langdon, D. G. (1999). Training. In D. G. Langdon, K. S. Whiteside, & M. M. McKenna (Eds.), Intervention resource guide: 50 performance improvement tools (pp 381–386). San Francisco: Jossey-Bass/Pfeiffer.

Langdon, D. G., Whiteside, K. S., & McKenna, M. M. (Eds.). (1999). Intervention resource guide: 50 performance improvement tools. San Francisco: Jossey-Bass/Pfeiffer.

McKay, J., & Wager, W. W. (2007). Electronic performance support systems: Visions and viewpoints. In R. A. Reiser & J. V. Dempsey (Eds.), Trends and issues in instructional design and technology (2nd ed., pp. 147–155). Upper Saddle River, NJ: Pearson, Merrill, Prentice Hall.

Molenda, M., & Pershing, J. A. (2004). An integrative approach to performance improvement and instructional systems design. TechTrends, 48(2), 26–32.

Prensky, M. (2001). Digital game-based learning. New York: McGraw Hill.

Rosenberg, M. J. (1995). Performance technology, performance support, and the future of training: A commentary. Performance Improvement Quarterly, 8(1), 94–99.

Rosenberg, M. J., Coscarelli, W. C., & Hutchison, C. S. (1999). The origins and evolution of the field. In H. D. Stolovitch & E. J. Keeps (Eds.), Handbook of human performance technology (2nd ed., pp. 24–46). San Francisco: Jossey Bass/Pfeiffer.

Rossett, A. (1999a). First things fast: A handbook for performance analysis. San Francisco: Jossey-Bass/Pfeiffer.

Rossett, A. (1999b). Analysis of human performance technology. In H. D. Stolovitch & E. J. Keeps (Eds.), Handbook of human performance technology (2nd ed., pp. 139–162). San Francisco: Jossey Bass/Pfeiffer.

Rossett, A. (2004). Taking lessons from business and government. eLearn Magazine, 2004(4), 1.

Rossett, A., & Gautier-Downes, J. (1991). Job aids. San Francisco: Jossey-Bass.

Rothwell, W. J. (1996a). ASTD models for human performance improvement: Roles, competencies, and outputs. Alexandria, VA: American Society for Training and Development.

Rothwell, W. J. (1996b). Beyond training and development: State-of-the-art strategies for enhancing human performance. New York: American Management Association.

Rothwell, W. J., Lindholm, J. E., & Wallick, W. G. (2003). What CEOs expect from corporate training. New York: American Management Association.

Stolovitch, H. D., & Keeps, E. J. (1999). What is Human Performance Technology? In H. D. Stolovitch & E. J. Keeps (Eds.), Handbook of human performance technology (2nd ed., pp. 3–23). San Francisco: Jossey Bass/Pfeiffer.

Stolovitch, H. D. (2007). The development and evolution of human performance improvement. In R. A. Reiser & J. V. Dempsey (Eds.), Trends and issues in instructional design and technology (2nd ed., pp. 134–146). Upper Saddle River, NJ: Pearson, Merrill, Prentice Hall.

Surry, D. W., Ensminger, D. C., & Haab, M. (2005). A model for integrating instructional technology into higher education. British Journal of Educational Technology, 36(2), 327–329.

Swanson, R. A. (1999a). Demonstrating return on investment in performance improvement projects. In H. D. Stolovitch & E. J. Keeps (Eds.), Handbook of human performance technology (2nd ed., pp. 813–839). San Francisco: Jossey Bass/Pfeiffer.

Swanson, R. A. (1999b). The foundations of human performance and implications for practice. Advances in Developing Human Resources 1(1), 1–28.

Thiagarajan, S., Estes, F., & Kemmerer, F. N. (1999). Designing compensation systems to motivate performance improvement. In H. D. Stolovitch & E. J. Keeps (Eds.), Handbook of human performance technology (2nd ed., pp. 411–429). San Francisco: Jossey Bass/Pfeiffer.

Torraco, R. J. (1999). Advancing our understanding or performance improvement. Advances in Developing Human Resources 1(1), 95–111.

Van Tiem, D. M., Moseley, J. L., & Dessigner, J. C. (2001). Performance improvement interventions: Enhancing people, processes, and organizations through performance technology. Silver Springs, MD: International Society for Performance Improvement.

Winer, L. R., Rushby, N., & Vazquez-Abad, J. (1999). Emerging trends in instructional interventions. In H. D. Stolovitch & E. J. Keeps (Eds.), Handbook of human performance technology (2nd ed., pp. 867–894). San Francisco: Jossey Bass/Pfeiffer.

Yelon, S. L. (1999). Live classroom instruction. In H. D. Stolovitch & E. J. Keeps (Eds.), Handbook of human performance technology (2nd ed., pp. 485–517). San Francisco: Jossey Bass/Pfeiffer.

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Surry Dan.jpgDaniel W. Surry is an Associate Professor of Instructional Design and Development at the University of South Alabama (USA). In that capacity, he advises master’s and doctoral students and teaches courses related to instructional design, performance technology, and large scale training systems. His research and consulting interests focus on the implementation of technology and the interaction between technology, people, and systems. He holds a Doctor of Education from The University of Georgia and a Master’s of Science from the University of South Alabama. Prior to joining the faculty at USA, he worked at the University of Southern Mississippi, the University of Alabama, and California State University, Fresno.
Stanfield Andy.jpgAt the time this chapter was written, Andy K. Stanfield served as Senior Instructional Designer in the University of South Alabama’s Online Learning Lab and was completing work toward a Doctor of Philosophy degree in Instructional Design and Development. He holds an M.A. in Literature from Jacksonville State University and an M.A. in Creative Writing from the University of South Alabama. He is an author, musician, teacher, and the founder and editor of Kyteflyte Productions.



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